Protein-based pharmaceuticals are one of the fastest growing sectors of the pharmaceutical pipeline. Monoclonal antibodies (mAbs) are expected to be among the leading candidates for biologic drugs in the future, with over 30 currently FDA-approved therapeutic products on the market. This class of proteins has the potential to treat many diseases, including various forms of cancer, autoimmune diseases, and life-threatening infections. However, mAbs and other protein-based therapeutics have inherent stability problems that can be problematic during manufacturing and storage. During processing, proteins may experience chemical, thermal, or mechanical stresses that lead to losses by chemical or physical degradation. During storage, the stresses may be reduced but proteins remain inherently labile molecules that can degrade during extended storage periods needed for commercial products. One example of physical degradation is aggregation. This, in particular, has the potential to jeopardize patient safety and drug efficacy if product administration leads to unwanted patient immune responses.
While the amino acid sequence ultimately dictates the three-dimensional structure of proteins, the surrounding solution environment also influences the conformational stability and propensity for non-native aggregation, i.e., aggregation via non-native conformational states. Solution pH, salt type and concentration, and the identity and concentration of other excipients may alter the chemical potential of the folded and unfolded states. Upon heating or applying other stresses, protein monomers (i.e., single protein molecules) can lose higher-order structure and biological function. As the same molecular forces that drive protein folding also drive protein aggregation, aggregated states are often expected to be lower in free energy than the folded or unfolded monomeric states when one operates at practical protein concentrations for therapeutic products. While thermodynamics may favor aggregates being the lowest free energy state, kinetics typically dictate the timescales and concentrations of the final aggregated populations. As such, measurement and prediction of aggregation rates is a major focus of effort during drug product development.
Non-native aggregation requires some degree of conformational change, as this allows otherwise buried regions of adjacent proteins to “bind” with one another. Larger aggregates can form via monomers adding to existing aggregates, or aggregates may coalesce with each other. As aggregation is a multi-step process, many stages have the potential to be the rate-limiting step. When one operates at temperatures significantly below the midpoint unfolding temperature(s), the unfolding/folding stage(s) will be pre-equilibrated because they occur much more quickly than the rate-limiting step(s) for aggregation. As such, unfolding thermodynamics will dictate the effective concentration of “reactive” protein molecules that are available to participate in the aggregation process, and this often results in aggregation rates that are highly sensitive to sample storage temperatures.
A priori prediction of aggregation rates for a protein in a given formulation remains an outstanding challenge for a variety of fundamental and practical reasons. The solution pH, choice of buffer species, and addition of salt and other excipients may affect conformational stability and/or protein-protein interactions, while temperature changes can dramatically effect conformational stability. Prior work has indicated that conformational stability is a key factor affecting aggregation rates in solution, as the midpoint temperature of thermal unfolding from differential scanning calorimetry, or the onset temperature of aggregation from scanning techniques, is often at least qualitatively predictive of aggregation rates across different formulations. However, there can also be a competing effect between changes in conformational stability and protein-protein interactions as one changes solution conditions such as pH.
A number of temperature-scanning techniques have been developed to at least qualitatively or semi-quantitatively monitor aggregation, but an inherent issue with these techniques is thermal history. For example, in the process of scanning through lower temperatures, one creates aggregates that can act as “seeds” to accelerate aggregation at subsequent (higher) temperatures, resulting in overestimation of aggregation rates. It is difficult to predict whether/when such seeding will occur, as simple changes in the formulation pH and ionic strength can alter aggregation mechanisms and “seeding” effects.
A large majority of biophysical techniques traditionally used to rapidly monitor aggregation use an indirect measure of monomer loss rates, providing only surrogate measures of aggregation. A direct measurement of monomer concentration necessitates separation of monomer from aggregate species or measuring a monomer-specific marker. For example, in spectroscopic techniques such as circular dichroism, ThT dye-binding or intrinsic fluorescence, the spectra are ensemble averages. Because the spectra have contributions from monomer and aggregate species, the spectral changes may or may not correlate with monomer consumption.
Indirect measures of monomer loss rates may also have bias, based on the measurement technique. For example, aggregation rates monitored using scattering techniques have a bias towards larger sized particles. In addition, dynamic and static scattering techniques are also convoluted with protein-protein interactions when one considers higher protein concentrations. As such, the putatively reported molecular weight or other measures of aggregate size are not generally correct under those conditions. This can also be a problem under conditions where protein monomers have long-ranged repulsions with one another. In addition, changes in ionic strength or pH can alter aggregation mechanisms, and produce large and heterogeneous aggregate populations that provide much larger scattering intensities compared to smaller-sized aggregates at identical monomer loss rates. These challenges are compounded if fragmentation occurs, as is relatively common for mAbs and other proteins.
Controlling and predicting unwanted degradation, including non-native aggregation, is a long-standing challenge in the effort to develop protein-based products. Aggregation rates are typically sensitive to temperature, pH, and the addition of excipients. Therefore, quantitatively comparing rates across multiple possible formulations is a key challenge in product development.